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A novel Bayesian modulation classification scheme is proposed for a single-antenna system over frequency-selective fading channels. The method is based on Gibbs sampling as applied to a latent Dirichlet Bayesian network (BN). The use of the proposed latent Dirichlet BN provides a systematic solution to the convergence problem encountered by the conventional Gibbs sampling approach for modulation classification...
In the next generation of wireless mobile communications, it can be visualized that heterogeneous networks including 3G cellular networks and WLAN are demanded to co-operate user-friendly in a seamless manner. Based on mobility of users, optimal session admission control for multimedia services is very important for improving performance in integrated 3G/WLAN networks. In this paper, a new dynamic...
In this paper, an effective framework for passive-blind color image forgery detection is proposed. It is a combination of image features extracted from image luminance by applying a rake-transform and from image chroma by using edge statistics. The efficacy of the image features has been tested over two color image datasets established for tampering detection. The proposed framework outweighs the...
Double JPEG compression detection is of significance in digital forensics. We propose an effective machine learning based scheme to distinguish between double and single JPEG compressed images. Firstly, difference JPEG 2D arrays, i.e., the difference between the magnitude of JPEG coefficient 2D array of a given JPEG image and its shifted versions along various directions, are used to enhance double...
A steganalysis system based on 2-D Markov chain of thresholded prediction-error image is proposed in this paper. Image pixels are predicted with their neighboring pixels, and the prediction-error image is generated by subtracting the prediction value from the pixel value and then thresholded with a predefined threshold. The empirical transition matrixes of Markov chain along the horizontal, vertical...
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